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   "source": [
    "# 60分钟入门深度学习工具-PyTorch(目录)"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**作者**：Soumith Chintala\n",
    "\n",
    "原文翻译自：https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html\n",
    "    \n",
    "中文翻译、注释制作：黄海广\n",
    "\n",
    "github：https://github.com/fengdu78\n",
    "\n",
    "代码全部测试通过。\n",
    "\n",
    "配置环境：PyTorch 1.0，Python 3.6\n",
    "\n",
    "主机：显卡：一块1080ti；内存：32g（注：绝大部分代码不需要GPU）\n",
    "![公众号](images/gongzhong.jpg)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 本教程的目标：\n",
    "\n",
    "* 在高层次上理解PyTorch的张量(Tensor)库和神经网络\n",
    "* 训练一个小型神经网络对图像进行分类\n",
    "* 本教程假设您对numpy有基本的了解\n",
    "\n",
    "**注意**： 务必确认您已经安装了 torch 和 torchvision 两个包。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 目录"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 1.[Pytorch是什么？](60分钟入门PyTorch-1.PyTorch是什么？.ipynb)\n",
    "* 2.[AUTOGRAD](60分钟入门PyTorch-2.AUTOGRAD.ipynb)\n",
    "* 3.[神经网络](60分钟入门PyTorch-3.神经网络.ipynb)\n",
    "* 4.[训练一个分类器](60分钟入门PyTorch-4.训练一个分类器.ipynb)\n",
    "* 5.[数据并行](60分钟入门PyTorch-5.数据并行.ipynb)"
   ]
  }
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